Triple

T18293267
Position Surface form Disambiguated ID Type / Status
Subject Series H E438167 entity
Predicate includes P1393 FINISHED
Object H.263 NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: H.263 | Statement: [Series H, includes, H.263]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: H.263
Context triple: [Series H, includes, H.263]
  • A. H.263 chosen
    H.263 is a video compression standard developed primarily for low-bitrate communication such as video conferencing and early internet video applications.
  • B. H.262
    H.262 is an international video compression standard, better known as MPEG-2 Part 2, widely used for digital television broadcasting and DVD video.
  • C. H.261
    H.261 is an early international video compression standard developed by the ITU-T for real-time video conferencing over ISDN and similar networks.
  • D. H.267
    H.267 is a member of the H.26x family of international video compression standards designed for efficient digital video coding.
  • E. H.324
    H.324 is an ITU-T multimedia communication protocol designed for real-time audio, video, and data transmission over circuit-switched telephone networks.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50100d6488190bbe73668df9c4046 completed April 19, 2026, 4:21 p.m.
Created at: April 10, 2026, 10:35 a.m.